Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/borda/ai-rig/debrief-codingnpx skills add Borda/AI-Rig --skill debrief-codinggit clone --depth 1 https://github.com/Borda/AI-RigWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/borda/ai-rig/debrief-coding)<a href="https://agentmods.dev/skills/borda/ai-rig/debrief-coding"><img src="https://agentmods.dev/badge/skills/borda/ai-rig/debrief-coding.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00069 | $0.02564 |
| Opus 5 | $0.00034 | $0.01282 |
| Sonnet 5 | $0.00014 | $0.00513 |
| Haiku 4.5 | $0.00007 | $0.00256 |
Grade A, and why
debrief-coding scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Read .cache/codemap/logs/ JSONL telemetry; analyze usage; write diagnostic report. Discover legacy flat shards + recursive claude/, codex/, direct/ trees; keep legacy records unattributed. Codex hooks supply runtime-scoped CLI/tool shards, no skill-start events; missing skill telemetry and cross-layer joins remain evidence gaps.
NOT for: validating codemap installation health/integration (use /codemap-py:integration audit); building/querying structural index (use /codemap-py:scan-codebase or /codemap-py:query-code).
Flags
--since <YYYY-MM-DD>— filter to records on or after this date (default: all)--session <id>— filter to a single session UUID--anonymize— runanonymize.pyon every log shard of all three layers (CLI, skill, tool) before reading; replaces qualified names with stable pseudonyms; keeps salt in.cache/codemap/logs/.salt(never included in output). Directory input preserves runtime topology below the export root and pseudonymizes shard session stems.--output <path>— write report to this path (default:.reports/codemap/debrief-<YYYY-MM-DD>.md)
Step 0: Verify logs exist
find .cache/codemap/logs -type f -name '*.jsonl' -print 2>/dev/null # timeout: 5000
No files → stop: "No codemap telemetry found. Run any /codemap-py:* skill or codemap-py query/index command to start collecting logs."
Per-session shards under logs/claude/, logs/codex/, logs/direct/: CLI cli_<session>.jsonl; skill skills_<session>.jsonl; tool tools_<session>.jsonl. Older flat shards = unattributed legacy evidence. Collect every matching shard recursively, not only root glob. Preserve topology; report overall, per-runtime, unattributed summaries. token_measurement unavailable: host hooks provide no token usage.
Step 1: Optionally anonymize
If --anonymize flag given:
Guard: anonymize every present CLI, skill, tool shard by passing log directory as --input; recursion covers flat + runtime shards. Copies land in .cache/codemap/export/ with same topology. anonymize.py refuses writes beside .salt; never target logs dir. Step 2 must not mix anonymized/original data or exempt a layer.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 190 lines · 0 tokens per session scan A ad1bdb68545f
debrief-coding is a skill published in the GitHub repository Borda/AI-Rig (26 stars, last pushed yesterday), licensed Apache-2.0. It adds 69 tokens to every session and 2,564 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
file-headers
MANDATORY for every coding agent (Claude Code, Codex, or any other) on every change-set — every applicable source file the agent creates or updates MUST start with the project's copyright/authorship header (file overview + exact author line). Use automatically whenever writing a new file or editing an existing one; do…
productivity-score
Calculate a productivity score using actual Agent Monitor metrics — session completion rates, cache efficiency (cacheread vs input), compaction pressure (baseline tokens), turn velocity (turncount / totalturndurationms), tool success ratio (PreToolUse vs PostToolUse), and the workflow intelligence API's complexity and…
budget-set
Define a spend budget for Claude Code and, optionally, create a cost alert rule that fires when usage crosses the limit, via POST /api/alerts/rules on the Agent Monitor dashboard. Reads current spend from /api/pricing/cost to size the budget sensibly and explains every rule field before writing. Use when setting a…
dashboard-status
Quick dashboard health and status overview — checks the Agent Monitor API (port 4820), reports session/agent/event counts from /api/stats, confirms WebSocket connectivity, reads the redacted hook status returned by /api/settings/info, and shows data freshness (last event timestamp). Use to verify the monitoring system…
dag-map
Render the multi-agent orchestration DAG for a session — parent→child subagent edges, tree depth, and fan-out — from the Agent Monitor workflow intelligence API. Cross-checks the orchestration dataset against the raw agent records and session detail. Use when visualizing how a session's agent structure was organized.
run-agent
Launch and supervise Claude Code or Codex through the CCAM Run API. Use when the user wants to start a monitored agent, select a model, approval policy, sandbox, or working directory, send a follow-up, inspect live output, resume a native session, or stop a dashboard-launched run.